The most frequent N-k line outages occur in motifs that can improve contingency selection

TL;DR

This paper identifies common outage patterns called motifs in power networks, demonstrating that focusing on these motifs improves the efficiency and accuracy of contingency planning and risk estimation.

Contribution

It introduces the concept of contingency motifs and shows that selecting N-k contingencies from these motifs captures most outage probabilities, enhancing contingency list efficiency.

Findings

Contingency motifs account for most multiple outage probabilities.

Motif-based contingency lists outperform exhaustive or random lists.

Using motifs improves risk estimation and contingency planning.

Abstract

Multiple line outages that occur together show a variety of spatial patterns in the power transmission network. Some of these spatial patterns form network contingency motifs, which we define as the patterns of multiple outages that occur much more frequently than multiple outages chosen randomly from the network. We show that choosing N-k contingencies from these commonly occurring contingency motifs accounts for most of the probability of multiple initiating line outages. This result is demonstrated using historical outage data for two transmission systems. It enables N-k contingency lists that are much more efficient in accounting for the likely multiple initiating outages than exhaustive listing or random selection. The N-k contingency lists constructed from motifs can improve risk estimation in cascading outage simulations and help to confirm utility contingency selection.